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Related Experiment Video

Updated: Aug 7, 2025

Tracking Infiltration Front Depth Using Time-lapse Multi-offset Gathers Collected with Array Antenna Ground Penetrating Radar
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Joint Aperture and Power Allocation Strategy for a Radar Network Localization System Based on Low Probability of

Chenyan Xue1,2, Ling Wang1, Daiyin Zhu1

  • 1Key Laboratory of Radar Imaging and Microwave Photonics, Ministry of Education, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China.

Sensors (Basel, Switzerland)
|March 11, 2023
PubMed
Summary
This summary is machine-generated.

This study introduces a joint aperture and power allocation scheme for Distributed Radar Network Localization Systems (DRNLS) to enhance Low Probability of Intercept (LPI) performance by considering random Aperture Resource Allocation (ARA) and Radar Cross Section (RCS). The proposed method optimizes power distribution, reducing element and power requirements while maintaining tracking performance.

Keywords:
Aperture Resource Allocation (ARA)Chance Constrained Programmin (CCP)Distributed Radar Network Localization System (DRNLS)Low Probability of Intercept (LPI)Radar Cross Section (RCS)Schleher Interception Factor

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Area of Science:

  • Radar Systems Engineering
  • Signal Processing
  • Optimization Theory

Background:

  • Distributed Radar Network Localization Systems (DRNLS) face limitations in survivability due to unaddressed random characteristics in Aperture Resource Allocation (ARA) and Radar Cross Section (RCS).
  • These random factors significantly impact power resource allocation, which is critical for achieving Low Probability of Intercept (LPI) performance in DRNLS.

Purpose of the Study:

  • To propose a joint aperture and power allocation scheme for DRNLS optimized for LPI performance.
  • To address the limitations of current DRNLS by incorporating random ARA and RCS characteristics into the allocation strategy.

Main Methods:

  • Development of a fuzzy random Chance Constrained Programming model for radar antenna aperture resource management (RAARM-FRCCP) to minimize elements.
  • Construction of a Chance Constrained Programming model for minimizing Schleher Intercept Factor (MSIF-RCCP) to optimize LPI performance while ensuring tracking requirements.

Main Results:

  • Demonstrated that uniform power distribution is not optimal when RCS exhibits randomness.
  • The proposed joint allocation scheme reduces the number of required elements and power compared to uniform distribution under similar tracking performance.
  • Lower confidence levels in the models allow for reduced power, enhancing LPI performance.

Conclusions:

  • The joint allocation scheme effectively improves LPI performance of DRNLS by accounting for random system characteristics.
  • The method provides a viable approach to optimize DRNLS power and aperture allocation for enhanced survivability and stealth.
  • The findings suggest a trade-off between confidence level, power consumption, and LPI effectiveness.